Kaggle Datasets are often too perfect for real-world scenarios.

I'm about to share a method for real-life data analysis.

You see …

… most of the time, a data analyst cleans and transforms data.

So … let’s practice that.

How?

Well … you can use ChatGPT.

Just write this prompt:

Create a downloadable CSV dataset of 10,000 rows of financial credit card transactions with 10 columns of customer data so I can perform some data analysis to segment customers.

Now…

Download the dataset and start your analysis.

You'll see that, most of the time…

… numbers don’t match.

There are no patterns.

Data is incorrect and doesn’t make sense.

And that’s good.

Now you know what a data analyst deals with.

Your job is to make sense of that dataset.

To create a story that justifies the numbers.

This is how you can mimic real-life work using A.I.

Creating a data science portfolio is a great way to showcase your skills and experience to potential employers. Here are some steps to help you create a strong data science portfolio:

1. Choose relevant projects: Select a few data science projects that demonstrate your skills and interests. These projects can be from your previous work experience, personal projects, or online competitions.

2. Clean and organize your code: Make sure your code is well-documented, organized, and easy to understand. Use comments to explain your thought process and the steps you took in your analysis.

3. Include a variety of projects: Try to include a mix of projects that showcase different aspects of data science, such as data cleaning, exploratory data analysis, machine learning, and data visualization.

4. Create visualizations: Data visualizations can help make your portfolio more engaging and easier to understand. Use tools like Matplotlib, Seaborn, or Tableau to create visually appealing charts and graphs.

5. Write project summaries: For each project, provide a brief summary of the problem you were trying to solve, the dataset you used, the methods you applied, and the results you obtained. Include any insights or recommendations that came out of your analysis.

6. Showcase your technical skills: Highlight the programming languages, libraries, and tools you used in each project. Mention any specific techniques or algorithms you implemented.

7. Link to your code and data: Provide links to your code repositories (e.g., GitHub) and any datasets you used in your projects. This allows potential employers to review your work in more detail.

8. Keep it updated: Regularly update your portfolio with new projects and skills as you gain more experience in data science. This will show that you are actively engaged in the field and continuously improving your skills.

By following these steps, you can create a comprehensive and visually appealing data science portfolio that will impress potential employers and help you stand out in the competitive job market.

Are you a data science beginner?

Here are 5 beginner-friendly data science project ideas

Loan Approval Prediction

Predict whether a loan will be approved based on customer demographic and financial data. This requires data preprocessing, feature engineering, and binary classification techniques.

Credit Card Fraud Detection

Detect fraudulent credit card transactions with a dataset that contains transactions made by credit cards. This is a good project for learning about imbalanced datasets and anomaly detection methods.

Netflix Movies and TV Shows Analysis

Analyze Netflix's movies and TV shows to discover trends in ratings, popularity, and genre distributions. Visualization tools and exploratory data analysis are key components here.

Sentiment Analysis of Tweets

Analyze the sentiment of tweets to determine whether they are positive, negative, or neutral. This project involves natural language processing and working with text data.

Weather Data Analysis

Analyze historical weather data from the National Oceanic and Atmospheric Administration (NOAA) to look for seasonal trends, weather anomalies, or climate change indicators. This project involves time series analysis and data visualization.

Join for more: https://news.1rj.ru/str/sqlproject

ENJOY LEARNING 👍👍

Today, I’m sharing three essential SQL projects to boost your resume

Energy Consumption Analysis:
Managed data from smart meters to analyze patterns and optimize efficiency. 🌱

Logistics and Supply Chain Management:
Designed a database to optimize delivery routes and forecast inventory. 🚚

Healthcare Management System:
Built a database for patient records, optimizing scheduling and performance analysis. 🏥

📊 According to the World Economic Forum, data analysis and database management are top skills for 2024.

FREE DATASET BUILDING YOUR PORTFOLIO ⭐

1. Supermarket Sales - https://lnkd.in/e86UpCMv
2.Credit Card Fraud Detection - https://lnkd.in/eFTsZDCW
3. FIFA 22 complete player dataset - https://lnkd.in/eDScdUUM
4. Walmart Store Sales Forecasting - https://lnkd.in/eVT6h-CT
5. Netflix Movies and TV Shows - https://lnkd.in/eZ3cduwK
6.LinkedIn Data Analyst jobs listings - https://lnkd.in/ezqxcmrE
7. Top 50 Fast-Food Chains in USA - https://lnkd.in/esBjf5u4
8. Amazon and Best Buy Electronics - https://lnkd.in/e4fBZvJ3
9. Forecasting Book Sales - https://lnkd.in/eXHN2XsQ
10. Real / Fake Job Posting Prediction - https://lnkd.in/e5SDDW9G

The first function you should learn in each data tool:

SQL: DELETE

Tableau: Pie chart with 10+ categories

Power BI: importing from Microsoft Paint (where the real visualization is done)

Excel: inserting pictures

Python: how to defend yourself against snakes

It’s important to focus on the functions you’ll use everyday.

5⃣ frequently Asked SQL Interview Questions with Answers in data analyst interviews

📍1. Write a SQL query to find the average purchase amount for each customer. Assume you have two tables: Customers (CustomerID, Name) and Orders (OrderID, CustomerID, Amount).

SELECT c.CustomerID, c. Name, AVG(o.Amount) AS AveragePurchase
FROM Customers c
JOIN Orders o ON c.CustomerID = o.CustomerID
GROUP BY c.CustomerID, c. Name;

📍2. Write a query to find the employee with the minimum salary in each department from a table Employees with columns EmployeeID, Name, DepartmentID, and Salary.

SELECT e1.DepartmentID, e1.EmployeeID, e1 .Name, e1.Salary
FROM Employees e1
WHERE Salary = (SELECT MIN(Salary) FROM Employees e2 WHERE e2.DepartmentID = e1.DepartmentID);

📍3. Write a SQL query to find all products that have never been sold. Assume you have a table Products (ProductID, ProductName) and a table Sales (SaleID, ProductID, Quantity).

SELECT p.ProductID, p.ProductName
FROM Products p
LEFT JOIN Sales s ON p.ProductID = s.ProductID
WHERE s.ProductID IS NULL;

📍4. Given a table Orders with columns OrderID, CustomerID, OrderDate, and a table OrderItems with columns OrderID, ItemID, Quantity, write a query to find the customer with the highest total order quantity.

SELECT o.CustomerID, SUM(oi.Quantity) AS TotalQuantity
FROM Orders o
JOIN OrderItems oi ON o.OrderID = oi.OrderID
GROUP BY o.CustomerID
ORDER BY TotalQuantity DESC
LIMIT 1;

📍5. Write a SQL query to find the earliest order date for each customer from a table Orders (OrderID, CustomerID, OrderDate).

SELECT CustomerID, MIN(OrderDate) AS EarliestOrderDate
FROM Orders
GROUP BY CustomerID;

🤔Are you looking for some new project ideas to include in your Portfolio❓

👉 Here are 3 unique ideas for you:

1️⃣ Summer Olympics
Dataset : https://www.kaggle.com/datasets/divyansh22/summer-olympics-medals

2️⃣ Food Nutrition
Dataset : https://www.kaggle.com/datasets/utsavdey1410/food-nutrition-dataset/data

3️⃣ Mental health
Dataset : https://www.kaggle.com/datasets/programmerrdai/mental-health-dataset/data

Datasets Name: Leukemia Classification

Datasets Name: Sign Language Detection using Images

Datasets Name: Football Player Detection YOLOv8

Datasets Name: Amazon Reviews Data 2023

Datasets Name: Gold Price & Relevant Metrics

Datasets Name: Ad Click Prediction Dataset